Long-range interactions and parallel scalability in molecular simulations

M. Patra, M.T. Hyvönen, E. Falck, M. Sabouri-Ghomi, I. Vattulainen, M.E.J. Karttunen

    Research output: Contribution to journalArticleAcademicpeer-review

    38 Citations (Scopus)


    Typical biomolecular systems such as cellular membranes, DNA, and protein complexes are highly charged. Thus, efficient and accurate treatment of electrostatic interactions is of great importance in computational modeling of such systems. We have employed the GROMACS simulation package to perform extensive benchmarking of different commonly used electrostatic schemes on a range of computer architectures (Pentium-4, IBM Power 4, and Apple/IBM G5) for single processor and parallel performance up to 8 nodes—we have also tested the scalability on four different networks, namely Infiniband, GigaBit Ethernet, Fast Ethernet, and nearly uniform memory architecture, i.e. communication between CPUs is possible by directly reading from or writing to other CPUs' local memory. It turns out that the particle–mesh Ewald method (PME) performs surprisingly well and offers competitive performance unless parallel runs on PC hardware with older network infrastructure are needed. Lipid bilayers of sizes 128, 512 and 2048 lipid molecules were used as the test systems representing typical cases encountered in biomolecular simulations. Our results enable an accurate prediction of computational speed on most current computing systems, both for serial and parallel runs. These results should be helpful in, for example, choosing the most suitable configuration for a small departmental computer cluster. Keywords: Molecular simulations; Parallel computing; Electrostatics; Lipid membranes; GROMACS
    Original languageEnglish
    Pages (from-to)14-22
    JournalComputer Physics Communications
    Issue number1
    Publication statusPublished - 2007


    Dive into the research topics of 'Long-range interactions and parallel scalability in molecular simulations'. Together they form a unique fingerprint.

    Cite this